Table 5 Scenario hypotheses and evolution of input variables in four possible scenarios for the Belgian livestock sector in 2050, in comparison with the current situation (2018–2022)

From: Narratives, trade-offs and scenarios to explore the livestock transition in Belgium

Scenario variables

BAU 2050

T1 2050

Land sharing

T2 2050

Land sparing - No Soy

T3 2050

Radical - No feed for food

Livestock populationsa

 Suckler cows

–26%

–50%

–100%

–100%

 Dairy cows

+7%

–30%

+22%

+14%

 Pigs

–30%

–30%

–74%

–91%

 Broilers

+55%

–30%

–75%

–89%

 Laying hens

+17%

–30%

–76%

–89%

Shares farming systemsb

 Organic

5% FL & 30% WAL

25%

30%

100%

 Extensive

Follows trends

Follows trends

70%

 Others

Follows trends

Follows trends

Reconfiguration of agricultural areac

 Agricultural land set aside for biodiversity

0%

20%

10%

10%

Optimisation of technical parametersd

 Dairy yields

+10%

+10%

+10%

+10%

 Feed conversion ratio - pigs and broilers

–10%

–10%

–10%

–10%

 Enteric fermentation – cattle and pigs

–10%

–10%

–10%

–10%

 Manure management

–15%

–15%

–15%

–15%

Diets and consumption patternse

 Diets considered

Current Belgian diet

TYFA diet

Belgian FBDG

EAT-Lancet diet

  1. Notes on scenario hypotheses.
  2. aLivestock populations: In scenario BAU, the pig population decreases by 30% as per the objectives set in the Flemish nitrogen decree for 2030. Other sectors decrease according to expected trends. In scenarios T2 and T3, the specialised dairy and suckler cow herds are replaced by a dual-purpose herd. In scenarios T2 and T3, monogastric populations evolve according to available feed sources: EU-origin soybean meal alternatives in the case of T2 and EU-origin cereal-equivalent coproducts in the case of T3.
  3. bShares of farming systems: In scenario BAU, the shares of organic systems are aligned on the regional objectives for organic agriculture, which are set for 2030 (thus expecting a 20-year delay in the achievement in such objectives, as observed following current trends).
  4. cReconfiguration of agricultural area: As the scenarios focus on the livestock sector, no specific assumptions are set on the distribution of crops within the Belgian agricultural area. Nevertheless, the linkages and interactions between agricultural land and animal production are not overlooked. They are checked through a series of indicators (grassland and forage feed self-sufficiency, and availability of animal manure for organic crop fertilisation). While the distribution of crop areas remains constant, a scenario hypothesis allows to set aside a share of agricultural land for non-productive biodiversity conservation. This area is taken in priority from arable land, leaving grasslands unaffected. This hypothesis has implications not only in terms of biodiversity, but also in terms of GHG emissions. On this aspect, the hypothesis is that the freed land is considered to be transformed into forests, thus leading to a null biodiversity damage score97 and to an additional storage of carbon100.
  5. dOptimisation of technical parameters: Gains in productivity and efficiency (feed conversion ratios and yields) are based on expert consultations59 and available literature101,102,103,104. Gains in enteric fermentation and manure management emissions are based on IPCC estimations105.
  6. eDiets and consumption patterns: Four different diets are considered across the scenarios in the modelling exercise, with one reference diet for each scenario: (1) current Belgian diet in scenario BAU; (2) TYFA diet scenario T1; (3) Belgian food-based dietary guidelines (FBDG) in scenario T2; (4) EAT-Lancet diet in scenario T3.